Data-Driven Control - Overview
Explore how machine learning optimization can discover models and effective controllers from data, revolutionizing control theory and engineering applications.
2019 ADSI Summer Workshop- Algorithmic Foundations of Learning and Control, Yinyu Ye
Explore advancements in online linear programming and learning, focusing on resource allocation, competitive ratios, and dynamic learning applications in control systems.
Exact Minimum Number of Bits to Stabilize a Linear System
Explore the mathematical foundations of stabilizing linear systems, focusing on the precise minimum number of bits required for effective control and decision-making in real-time scenarios.
Control Fundamentals
Explore key principles and applications of control theory in reinforcement learning, focusing on fundamental concepts and their practical implications.
Control Theory and COVID-19: Models
Explores modeling techniques for infectious diseases like COVID-19, emphasizing their importance in control efforts. Discusses imperfect models' utility and various resources for understanding disease spread.
Data-Driven Control - Balanced Proper Orthogonal Decomposition
Explore balancing proper orthogonal decomposition (BPOD) for approximating balanced truncation in high-dimensional systems, enhancing control strategies for complex data-driven applications.
Controllability - Control Bootcamp
Explore linear system controllability through intuitive examples and the controllability matrix rank test. Learn key concepts for understanding and analyzing system control.
Stabilization of Nonlinear Systems by Oscillating Controls with Application
Explore nonlinear system stabilization using oscillating controls, with applications in nonholonomic and fluid dynamics. Covers control design, Lie brackets, and energy cascades.
Control Theory and Large Deviation Principles for PDEs
Explore control theory and large deviation principles for PDEs, covering IID cases, contraction principles, rate functions, and applications to random forces and controllability.
Tame Phenomena Over the Real Field - Lecture 6
Explore control theory concepts including flows, log spirals, limit cycles, and restricted analytic functions in this advanced graduate-level lecture on tame phenomena.
Tame Control Theory
Explore tame geometry in control theory, covering basic definitions, motivation, logic, and vector fields. Gain insights into descriptive set theory and generic structures.
Feedback Control Theory - Architectures and Tools for Real-Time Decision Making II
Explore advanced control systems, design patterns, and optimization techniques for real-time decision making in complex systems. Learn about PID control, robustness, and temporal logic.
Sufficient Geometric Conditions for the Null-Controllability of Evolution
Explore geometric conditions for null-controllability in evolution equations with Gelfand-Shilov smoothing, including uncertainty principles and applications to fractional harmonic oscillators.
Simultaneous Control of Ensembles of Dynamical Systems
Control strategies for managing multiple dynamic systems simultaneously, focusing on mathematical approaches and applications in various fields.
Tame Control Theory - Lecture 5
Explore advanced concepts in tame control theory, focusing on phenomena over real fields. Delve into graduate-level mathematical analysis and applications.
Tame Phenomena Over the Real Field - Graduate Course Lecture 1
Explore fundamental concepts of tame control theory, focusing on real field applications and advanced mathematical principles in this graduate-level lecture.
Control Theory of Stochastic Distributed Parameter Systems - Some Recent Progresses
Recent advancements in stochastic distributed parameter control systems, focusing on controllability of hyperbolic equations and Pontryagin-type maximum principle for controlled stochastic evolution equations.
Reachable States for Infinite Dimensional Linear Systems - Old and New
Explore reachable states in infinite dimensional linear systems, examining both established concepts and recent developments in mathematical control theory.
Black Hole Battles - Control Theory III
Explore advanced control theory concepts for navigating spacecraft through black hole fields in this physics-based game development tutorial.
Black Hole Battles - Control Theory II
Explore cost evaluation in ship navigation through black hole fields using control theory principles.
Black Hole Battles - Control Theory I
Explore control theory applications in game development, enhancing enemy AI for a physics-based space navigation game featuring black holes.